sujithvn / carnd-traffic-sign-classifier-project Goto Github PK

This project is submitted as part of the Udacity Self Driving Car Nanodegree program.

Please refer the Write-Up for the submission check points and the responses/findings.

The code is available both in Notebook and HTML format.

In this project, we use deep neural networks and convolutional neural networks to classify traffic signs. We will train and validate a model so it can classify traffic sign images using the German Traffic Sign Dataset. After the model is trained, we will then try out your model on images of German traffic signs that we find on the web.

The goals / steps of this project are the following:

• Load the data set
• Explore, summarize and visualize the data set
• Pre-process the data including Augmentation.
• Design, train and test a model architecture
• Use the model to make predictions on new images
• Analyze the softmax probabilities of the new images
• Summarize the results with a written report

This lab requires:

• CarND Term1 Starter Kit

The lab environment can be created with CarND Term1 Starter Kit. Click here for the details.